MLR-DBPFN: A Multi-Scale Low Rank Deep Back Projection Fusion Network for Anti-Noise Hyperspectral and Multispectral Image Fusion

Fusing low spatial resolution (LR) hyperspectral (HS) data and high spatial resolution (HR) multispectral (MS) data aims to obtain HR HS data. However, due to bad weather and the aging of sensor equipment, HS images usually contain a lot of noise, e.g., Gaussian noise, strip noise, and mixed noise,...

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Veröffentlicht in:	IEEE transactions on geoscience and remote sensing 2022, Vol.60, p.1-14
Hauptverfasser:	Sun, Weiwei, Ren, Kai, Meng, Xiangchao, Yang, Gang, Xiao, Chenchao, Peng, Jiangtao, Huang, Jingfeng
Format:	Artikel
Sprache:	eng
Schlagworte:	Ageing Aging Antinoise Computer vision Convolution Data integration deep learning Feature extraction hyperspectral (HS) Image fusion Image processing Image quality Matrix decomposition multiscale low rank (MLR) multispectral (MS) Noise Noise measurement Noise reduction Random noise Resolution Spatial data Spatial discrimination Spatial resolution Spectra Weathering
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